The current preferred method for optimizing the design of components is by the use of Computer Aided Engineering (“CAE”). Traditional CAE methods typically utilize finite element analysis (“FEA”), which in turn is based on computer models of the part.
Currently, CAE methods typically rely on theoretical mathematical models run through a computer simulation. The results of the analysis are only as accurate as the model. Accuracy of the model is typically a function of the time, effort and skill an engineer puts into creating the model. Model accuracy is also dependent on the accuracy and inherent assumptions of the code.
Once the model is completed, it often must be calibrated to the physical embodiment that it represents in order to produce realistic failure mode and durability predictions. Calibration is typically based on data collected from discrete points through the use of strain gauges on a physical model. Calibrating the model based on this “strain gauge method” is subject to many inaccuracies. Strain gauge size, direction, and placement are key contributors to inaccuracy. Strain gauges are sometimes difficult to install on certain surfaces with high stress concentrations (fillet, hole, etc.) and sometimes impractical for use in measuring strain that is induced under certain circumstances (e.g., high strain gradient). Strain gauges are generally referred to as “point-measuring sensors.” The strain gauge gridlines measure only the deformation component in its application direction and at its location. It reports only the average value of measured deformation over the area occupied by the strain gauge. Since strain gauges measure strain at discrete points, poor selection of the strain gauge location can contribute to inaccuracy. Extrapolation of strain gauge results on a three dimensional part with odd geometry can also result in an inaccurate model. In addition, strain gauge instrumentation of larger parts can take up substantial amounts of engineer and technician time.
It would be desirable, therefore, to provide a method for calibrating and verifying mathematical models that is faster, more flexible, more accurate, less dependant on technician skill and less expensive than traditional methods.